Cargando…
Cleaning by clustering: methodology for addressing data quality issues in biomedical metadata
BACKGROUND: The ability to efficiently search and filter datasets depends on access to high quality metadata. While most biomedical repositories require data submitters to provide a minimal set of metadata, some such as the Gene Expression Omnibus (GEO) allows users to specify additional metadata in...
Autores principales: | Hu, Wei, Zaveri, Amrapali, Qiu, Honglei, Dumontier, Michel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5604298/ https://www.ncbi.nlm.nih.gov/pubmed/28923003 http://dx.doi.org/10.1186/s12859-017-1832-4 |
Ejemplares similares
-
SIENA: Semi-automatic semantic enhancement of datasets using concept recognition
por: Grigoriu, Andreea, et al.
Publicado: (2021) -
Predicting structured metadata from unstructured metadata
por: Posch, Lisa, et al.
Publicado: (2016) -
Predicting structured metadata from unstructured metadata
por: Posch, Lisa, et al.
Publicado: (2016) -
A metadata schema for data objects in clinical research
por: Canham, Steve, et al.
Publicado: (2016) -
CLEAN: CLustering Enrichment ANalysis
por: Freudenberg, Johannes M, et al.
Publicado: (2009)